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Build and maintain scalable data pipelines in Python and SQL, orchestrated with Airflow and landing in AWS data lakes and warehouses. Work on lakehouse patte...
Senior Data Engineer (AWS) | Qbitech Responsibilities check_circle Build and maintain Python and SQL pipelines orchestrated with Airflow. check_circle Design and improve ingestion, transformation, and serving layers on AWS data lakes and warehouses. check_circle Implement and enforce data quality checks, data contracts, and schema evolution practices. check_circle Optimize large-scale batch and streaming jobs with Spark/PySpark and modern table formats. check_circle Apply CI/CD and infrastructure-as-code practices to data workflows. check_circle Improve observability with monitoring, alerting, and SLI/SLO thinking. check_circle Collaborate on secure handling of data, access control, and governance. shield Requirements 5+ years of experience building production ETL/ELT pipelines at scale. Strong Python, SQL, and data modeling skills. Hands-on experience with Airflow and Apache Spark/PySpark. Practical AWS experience with S3 and data warehouse services. Experience with data quality frameworks, schema evolution, and CI/CD. Familiarity with Iceberg, Delta Lake, dbt, Kafka, or Kinesis is a plus. Experience in a regulated, high-scale, or analytics-heavy environment is a plus. What will be your next steps? 01 chat_bubble Quick non-technical conversation Our initial conversation is a brief, non-technical discussion to understand your background and career aspirations. We're keen to learn about your communication style and how you approach teamwork and decision-making. 02 code 60 to 90 minutes technical interview This in-depth technical assessment, lasting 60 to 90 minutes, is designed to evaluate your specific skills and expertise. We will present you with challenges relevant to our client’s requirements. 03 groups Client interview In this stage, you will meet directly with the client for a final technical discussion. This interview will be similar in format to our internal technical assessment, allowing the client to see firsthand how your expertise aligns with their specific project needs and team. 04 workspace_premium Offer Congratulations on successfully completing our evaluation process. We are pleased to extend an offer and recommend you to our clients. Fill in your details below. We'll get back to you shortly. 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